Authentication of packetized audio signals

ABSTRACT

The present disclosure is generally directed a data processing system for authenticating packetized audio signals in a voice activated computer network environment. The data processing system can improve the efficiency and effectiveness of auditory data packet transmission over one or more computer networks by, for example, disabling malicious transmissions prior to their transmission across the network. The present solution can also improve computational efficiency by disabling remote computer processes possibly affected by or caused by the malicious audio signal transmissions. By disabling the transmission of malicious audio signals, the system can reduce bandwidth utilization by not transmitting the data packets carrying the malicious audio signal across the networks.

CROSS-REFERENCES TO RELATED APPLICATIONS

This application claims the benefit of priority under 35 U.S.C. § 120 asa continuation of U.S. patent application Ser. No. 15/395,729, filedDec. 30, 2016, which is hereby incorporated by reference herein in itsentirety.

BACKGROUND

Excessive network transmissions, packet-based or otherwise, of networktraffic data between computing devices can prevent a computing devicefrom properly processing the network traffic data, completing anoperation related to the network traffic data, or responding timely tothe network traffic data. The excessive network transmissions of networktraffic data can also complicate data routing or degrade the quality ofthe response if the responding computing device is at or above itsprocessing capacity, which may result in inefficient bandwidthutilization. A portion of the excessive network transmissions caninclude malicious network transmissions.

SUMMARY

The present disclosure is generally directed to authenticatingpacketized audio signals in a voice activated computer networkenvironment to reduce the amount of excessive network transmissions. Anatural language processor component executed by a data processingsystem can receive data packets. The data packets can include an inputaudio signal detected by a sensor of a client computing device. Thenatural language processor component can parse the input audio signal toidentify a request and a trigger keyword corresponding to the request. Anetwork security appliance can analyze one or more characteristics ofthe input audio signal. Based on the characteristics, the networksecurity appliance can set an alarm condition. The network securityappliance can provide, to a content selector component of the dataprocessing system, an indication of the alarm condition. The contentselector component can select, based on the alarm condition, a contentitem via a real-time content selection process. An audio signalgenerator component executed by the data processing system can generatean output signal comprising the content item. An interface of the dataprocessing system can transmit data packets comprising the output signalgenerated by the audio signal generator component to cause an audiodriver component executed by the client computing device to drive aspeaker of the client computing device to generate an acoustic wavecorresponding to the output signal. The data processing system canreceive a response audio signal. The response audio signal is receivedin response to the output signal generated by the client computingdevice. The response audio signal can include characteristics, which areanalyzed by the network security appliance. Based on the characteristicsof the response audio signal, the network security appliance canterminate or suspend a communication session between a service providerand client computing device.

According to one aspect of the disclosure, a system for authenticatingpacketized audio signals in a voice activated computer networkenvironment can include a natural language processor component that isexecuted by a data processing system. The natural language processor canreceive, via an interface of the data processing system, data packetsthat include an input audio signal detected by a sensor of a clientdevice. The natural language processor component can parse the inputaudio signal to identify a request and a trigger keyword correspondingto the request. The system can include a direct action applicationprogramming interface of the data processing system that can generate,based on the trigger keyword, a first action data structure responsiveto the request. The system can also include a network security appliancethat can compare the first action data structure with a firstcharacteristic of the input audio signal to detect an alarm condition.The system can include a content selector component that is executed bythe data processing system. The content selector can receive the triggerkeyword identified by the natural language processor and the indicationof the first alarm condition, and select, based on the trigger keywordand the indication, a content item. The network security appliance canreceive data packets carrying a response audio signal transmittedbetween the client device and a conversational application programminginterface that established a communication session with the clientdevice. The network security appliance can compare a secondcharacteristic of the response audio signal with the firstcharacteristic of the input audio signal to detect a second alarmcondition. The network security appliance can transmit, based on thesecond alarm condition, an instruction to the third party providerdevice to disable the communication session established with the clientdevice.

According to another aspect of the disclosure a method forauthenticating packetized audio signals in a voice activated computernetwork environment can include receiving, by a natural languageprocessor component executed by a data processing system, data packetsincluding an input audio signal detected by a sensor of a client device.The method can also include parsing, by the natural language processorcomponent, the input audio signal to identify a request and a triggerkeyword corresponding to the request. The method can include generating,by a direct action application programming interface of the dataprocessing system, based on the trigger keyword, a first action datastructure responsive to the request. The method can include comparing,by a network security appliance, the first action data structure with afirst characteristic of the input audio signal to detect an alarmcondition. The method can include selecting, by a content selectorcomponent executed by the data processing system, a content item basedon the trigger keyword and the alarm condition. The method can includereceiving, by the network security appliance, data packets carrying aresponse audio signal transmitted between the client device and aconversational application programming interface that established acommunication session with the client device. The method can includecomparing, by the network security appliance, a second characteristic ofthe response audio signal with the first characteristic of the inputaudio signal to detect a second alarm condition. The method can includetransmitting, by the network security appliance, based on the secondalarm condition, an instruction to the third party provider device todisable the communication session established with the client device inresponse to the interaction with the content item.

According to one aspect of the disclosure, a system for authenticatingpacketized audio signals in a voice activated computer networkenvironment can include a natural language processor component that isexecuted by a data processing system. The natural language processor canreceive, via an interface of the data processing system, data packetsthat include an input audio signal detected by a sensor of a clientdevice. The natural language processor component can parse the inputaudio signal to identify a request and a trigger keyword correspondingto the request. The system can include a direct action applicationprogramming interface of the data processing system that can generate,based on the trigger keyword, a first action data structure responsiveto the request. The system can also include a network security appliancethat can compare the first action data structure with a firstcharacteristic of the input audio signal to detect an alarm condition.The system can include a content selector component that is executed bythe data processing system. The content selector can receive the triggerkeyword identified by the natural language processor and the indicationof the first alarm condition, and select, based on the trigger keywordand the indication, a content item. The network security appliance canreceive data packets carrying a response audio signal transmittedbetween the client device and a conversational application programminginterface that established a communication session with the clientdevice. The network security appliance can compare a secondcharacteristic of the response audio signal with the firstcharacteristic of the input audio signal to detect a pass condition. Thenetwork security appliance can transmit, based on the second alarmcondition, an instruction to the third party provider device to continuethe communication session established with the client device.

These and other aspects and implementations are discussed in detailbelow. The foregoing information and the following detailed descriptioninclude illustrative examples of various aspects and implementations andprovide an overview or framework for understanding the nature andcharacter of the claimed aspects and implementations. The drawingsprovide illustration and a further understanding of the various aspectsand implementations, and are incorporated in and constitute a part ofthis specification.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings are not intended to be drawn to scale. Likereference numbers and designations in the various drawings indicate likeelements. For purposes of clarity, not every component may be labeled inevery drawing. In the drawings:

FIG. 1 depicts an example system to perform authentication of packetizedaudio signals in a voice activated data packet (or other protocol) basedcomputer network environment;

FIG. 2 illustrates a flow diagram illustrating an example operation of asystem to perform authentication of packetized audio signals;

FIG. 3 illustrates an example method to authenticate packetized audiosignals in a voice activated data packet (or other protocol) basedcomputer network environment using the system illustrated in FIG. 1; and

FIG. 4 is a block diagram illustrating a general architecture for acomputer system that may be employed to implement elements of thesystems and methods described and illustrated herein.

DETAILED DESCRIPTION

Following below are more detailed descriptions of various conceptsrelated to, and implementations of, methods, apparatuses, and systemsfor the authentication of packetized audio signals. The various conceptsintroduced above and discussed in greater detail below may beimplemented in any of numerous ways.

The present disclosure is generally directed a data processing systemfor authenticating packetized audio signals in a voice activatedcomputer network environment. The data processing system can improve theefficiency and effectiveness of auditory data packet transmission overone or more computer networks by, for example, disabling malicioustransmissions prior to their transmission across the network. Thepresent solution can also improve computational efficiency by disablingremote computer processes possibly affected by or caused by themalicious audio signal transmissions. By disabling the transmission ofmalicious audio signals, the system can reduce bandwidth utilization bynot transmitting the data packets carrying the malicious audio signalacross the networks. Processing the naturally spoken audio signal can bea computationally intensive task. By detecting possibly malicious audiosignals, the system can reduce computational waste by enabling thesystem to skip or temporarily skip the processing of possibly maliciousaudio signals. The system can reduce computational waste by disablingcommunication sessions when the malicious activity is detected.

The systems and methods described herein can include a data processingsystem that receives an audio input query, which can also be referred toas an audio input signal. From the audio input query the data processingsystem can identify a request and a trigger keyword corresponding to therequest. The system can generate action data structures based on theaudio input query. The system can also measure characteristics of theaudio input query. The system can determine if the characteristics ofthe audio input query match predicted or expected characteristics of theaudio input query. If the characteristics do not match the expectedcharacteristics, the system can select a content item that istransmitted back to the source of the audio input query. A communicationsession can be started with the source. The content item can include anoutput signal that can be played through a speaker associated with thesource. The system can receive a response audio signal to the contentitem. The response audio signal can also include characteristics thatare compared by the system to expected characteristics. If thecharacteristics of the response audio signal do not match the expectedcharacteristics, the system can disable the communication sessions withthe source and prevent the source from initiating communication sessionswith third-party service providers or content providers, which savesnetwork bandwidth, reduces processor utilization, and saves electricalpower.

The present solution can prevent the transmission of insecureaudio-based user interactions by authenticating the interaction.Securing audio-based user interactions can prevent malicious processesfrom being executed under the user (or other's) account. Preventing theexecution of malicious processes can also reduce network bandwidthutilization and reduce processor utilization or load. The presentsolution can reduce network bandwidth utilization by terminating thetransmission of unauthorized audio-based user interactions.

FIG. 1 depicts an example system 100 to perform authentication ofpacketized audio signals in a voice activated data packet (or otherprotocol) based computer network environment. The system 100 can includeat least one data processing system 105. The data processing system 105can include at least one server having at least one processor. Forexample, the data processing system 105 can include a plurality ofservers located in at least one data center or server farm. The dataprocessing system 105 can determine from an audio input signal a requestand a trigger keyword associated with the request. Based on the requestand trigger keyword the data processing system 105 can determine orselect a thread that includes a plurality of sequence-dependentoperations and can select content items (and initiate other actions asdescribed herein) in an order that does not match the sequence ofdependent operations, for example as part of a voice activatedcommunication or planning system. The content items can include one ormore audio files that when rendered provide an audio output or acousticwave. The content items can include other content (e.g., text, video, orimage content) in addition to audio content.

The data processing system 105 can include multiple, logically-groupedservers and facilitate distributed computing techniques. The logicalgroup of servers may be referred to as a data center, server farm or amachine farm. The servers can be geographically dispersed. A data centeror machine farm may be administered as a single entity, or the machinefarm can include a plurality of machine farms. The servers within eachmachine farm can be heterogeneous—one or more of the servers or machinescan operate according to one or more type of operating system platform.The data processing system 105 can include servers in a data center thatare stored in one or more high-density rack systems, along withassociated storage systems, located for example in an enterprise datacenter. The data processing system 105 with consolidated servers in thisway can improve system manageability, data security, the physicalsecurity of the system, and system performance by locating servers andhigh performance storage systems on localized high performance networks.Centralization of all or some of the data processing system 105components, including servers and storage systems, and coupling themwith advanced system management tools allows more efficient use ofserver resources, which saves power and processing requirements andreduces bandwidth usage.

The data processing system 105 can include at least one natural languageprocessor (NLP) component 110, at least one interface 115, at least onenetwork security appliance 123, at least one content selector component125, at least one audio signal generator component 130, at least onedirect action application programming interface (API) 135, at least onesession handler component 140, at least one communication API 136, andat least one data repository 145. The NLP component 110, interface 115,network security appliance 123, content selector component 125, audiosignal generator component 130, direct action API 135, and sessionhandler component 140 can each include at least one processing unit,server, virtual server, circuit, engine, agent, appliance, or otherlogic device such as programmable logic arrays configured to communicatewith the data repository 145 and with other computing devices (e.g., theclient computing device 150, the content provider computing device 155,or the service provider computing device 160) via the at least onecomputer network 165. The network 165 can include computer networks suchas the internet, local, wide, metro or other area networks, intranets,satellite networks, other computer networks such as voice or data mobilephone communication networks, and combinations thereof.

The session handler component 140 can establish a communication sessionbetween the data processing system 105 and the client computing device150. The session handler component 140 can generate the communicationsession based on receiving an input audio signal from the computingdevice 150. The session handler component 140 can set the initialduration of the communication session base on the time of day, locationof the client computing device 150, context of the input audio signal,or a voiceprint. The session handler component 140 can terminate thecommunication session after expiration of the session. Authenticationmay only be needed once per communication session. For example, the dataprocessing system 105 can determine that there was a previous successfulauthentication during the communication session, and not require anadditional authentication until after the communication session expires.

The network 165 can include or constitute a display network, e.g., asubset of information resources available on the internet that areassociated with a content placement or search engine results system, orthat are eligible to include third party content items as part of acontent item placement campaign. The network 165 can be used by the dataprocessing system 105 to access information resources such as web pages,web sites, domain names, or uniform resource locators that can bepresented, output, rendered, or displayed by the client computing device150. For example, via the network 165 a user of the client computingdevice 150 can access information or data provided by the contentprovider computing device 155 or the service provider computing device160.

The network 165 can include, for example a point-to-point network, abroadcast network, a wide area network, a local area network, atelecommunications network, a data communication network, a computernetwork, an ATM (Asynchronous Transfer Mode) network, a SONET(Synchronous Optical Network) network, a SDH (Synchronous DigitalHierarchy) network, a wireless network or a wireline network, andcombinations thereof. The network 165 can include a wireless link, suchas an infrared channel or satellite band. The topology of the network165 may include a bus, star, or ring network topology. The network 165can include mobile telephone networks using any protocol or protocolsused to communicate among mobile devices, including advanced mobilephone protocol (“AMPS”), time division multiple access (“TDMA”),code-division multiple access (“CDMA”), global system for mobilecommunication (“GSM”), general packet radio services (“GPRS”) oruniversal mobile telecommunications system (“UMTS”). Different types ofdata may be transmitted via different protocols, or the same types ofdata may be transmitted via different protocols.

The client computing device 150, the content provider computing device155, and the service provider computing device 160 can each include atleast one logic device such as a computing device having a processor tocommunicate with each other or with the data processing system 105 viathe network 165. The client computing device 150, the content providercomputing device 155, and the service provider computing device 160 caneach include at least one server, processor or memory, or a plurality ofcomputation resources or servers located in at least one data center.The client computing device 150, the content provider computing device155, and the service provider computing device 160 can each include atleast one computing device such as a desktop computer, laptop, tablet,personal digital assistant, smartphone, portable computer, thin clientcomputer, virtual server, or other computing device.

The client computing device 150 can include at least one sensor 151, atleast one transducer 152, at least one audio driver 153, and at leastone speaker 154. The sensor 151 can include a microphone or audio inputsensor. The sensor 151 can also include at least one of a GPS sensor,proximity sensor, ambient light sensor, temperature sensor, motionsensor, accelerometer, or gyroscope. The transducer 152 can convert theaudio input into an electronic signal. The audio driver 153 can includea script or program executed by one or more processors of the clientcomputing device 150 to control the sensor 151, the transducer 152 orthe audio driver 153, among other components of the client computingdevice 150 to process audio input or provide audio output. The speaker154 can transmit the audio output signal.

The client computing device 150 can be associated with an end user thatenters voice queries as audio input into the client computing device 150(via the sensor 151) and receives audio output in the form of a computergenerated voice that can be provided from the data processing system 105(or the content provider computing device 155 or the service providercomputing device 160) to the client computing device 150, output fromthe speaker 154. The computer generated voice can include recordingsfrom a real person or computer generated language.

The content provider computing device 155 can provide audio basedcontent items for display by the client computing device 150 as an audiooutput content item. The content item can include an offer for a good orservice, such as a voice based message that states: “Would you like meto order you a taxi?” For example, the content provider computing device155 can include memory to store a series of audio content items that canbe provided in response to a voice based query. The content providercomputing device 155 can also provide audio based content items (orother content items) to the data processing system 105 where they can bestored in the data repository 145. The data processing system 105 canselect the audio content items and provide (or instruct the contentprovider computing device 155 to provide) the audio content items to theclient computing device 150. The content can include security questionsthat are generated to authenticate the user of the client computingdevice 150. The audio based content items can be exclusively audio orcan be combined with text, image, or video data.

The service provider computing device 160 can include at least oneservice provider natural language processor (NLP) component 161 and atleast one service provider interface 162. The service provider NLPcomponent 161 (or other components such as a direct action API of theservice provider computing device 160) can engage with the clientcomputing device 150 (via the data processing system 105 or bypassingthe data processing system 105) to create a back-and-forth real-timevoice or audio based conversation (e.g., a session) between the clientcomputing device 150 and the service provider computing device 160. Forexample, the service provider interface 162 can receive or provide datamessages to the direct action API 135 of the data processing system 105.The service provider computing device 160 and the content providercomputing device 155 can be associated with the same entity. Forexample, the content provider computing device 155 can create, store, ormake available content items for a car sharing service, and the serviceprovider computing device 160 can establish a session with the clientcomputing device 150 to arrange for a delivery of a taxi or car of thecar share service to pick up the end user of the client computing device150. The data processing system 105, via the direct action API 135, theNLP component 110 or other components can also establish the sessionwith the client computing device, including or bypassing the serviceprovider computing device 160, to arrange for example for a delivery ofa taxi or car of the car share service.

The service provider device 160, the content provider device 155, andthe data processing system 105 can include a conversational API 136. Theend user can interact, via a voice conversation, with the content itemsand the data processing system 105 via a communication session. Thevoice conversation can be between the client device 150 and theconversational API 136. The conversational API 136 can be executed bythe data processing system 105, service provider 160, or contentprovider 155. The data processing system 105 can obtain additionalinformation about the end user's interaction with the content directlywhen the data processing system executes the conversational API 136.When the service provider 160 or content provider provide 155 executethe conversational API 136, the communication session can either berouted through the data processing system 105, or the respectiveentities can forward data packets of the communication session to thedata processing system 105. The networking security appliance describedherein can terminate the communication session when the conversationalAPI 136 is executed by the data processing system 105. The networkingsecurity appliance 105 can send instructions to the service provider 160or content provider 155 to terminate (or otherwise disable) thecommunication session when the service provider 160 or content provider155 execute the conversational API 136.

The data repository 145 can include one or more local or distributeddatabases and can include a database management system. The datarepository 145 can include computer data storage or memory and can storeone or more parameters 146, one or more policies 147, content data 148,or templates 149 among other data. The parameters 146, policies 147, andtemplates 149 can include information such as rules about a voice basedsession between the client computing device 150 and the data processingsystem 105 (or the service provider computing device 160). The contentdata 148 can include content items for audio output or associatedmetadata, as well as input audio messages that can be part of one ormore communication sessions with the client computing device 150.

The data processing system 105 can include an application, script orprogram installed at the client computing device 150, such as an app tocommunicate input audio signals to the interface 115 of the dataprocessing system 105 and to drive components of the client computingdevice to render output audio signals. The data processing system 105can receive data packets or other signals that include or identify anaudio input signal. For example, the data processing system 105 canexecute or run the NLP component 110 to receive the audio input signal.The audio input signal can be detected by the sensor 151 (e.g., amicrophone) of the client computing device. The NLP component 110 canconvert audio input signal into recognized text by comparing the inputsignal against a stored, representative set of audio waveforms andchoosing the closest matches. The representative waveforms can begenerated across a large set of input signals. The user can provide someof the input signals. Once the audio signal is converted into recognizedtext, the NLP component 110 can match the text to words that areassociated, for example via a learning phase, with actions that thesystem 200 can make. Via the transducer 152, the audio driver 153, orother components, the client computing device 150 can provide the audioinput signal to the data processing system 105 (e.g., via the network165) where it can be received (e.g., by the interface 115) and providedto the NLP component 110 or stored in the data repository 145 as contentdata 148.

The NLP component 110 can obtain the input audio signal. From the inputaudio signal, the NLP component 110 can identify at least one request orat least one trigger keyword corresponding to the request. The requestcan indicate intent or subject matter of the input audio signal. Thetrigger keyword can indicate a type of action likely to be taken. Forexample, the NLP component 110 can parse the input audio signal toidentify at least one request to leave home for the evening to attenddinner and a movie. The trigger keyword can include at least one word,phrase, root or partial word, or derivative indicating an action to betaken. For example, the trigger keyword “go” or “to go to” from theinput audio signal can indicate a need for transport. In this example,the input audio signal (or the identified request) does not directlyexpress an intent for transport; however, the trigger keyword indicatesthat transport is an ancillary action to at least one other action thatis indicated by the request.

The content selector component 125 can obtain this information from thedata repository 145, where it can be stored as part of the content data148. The content selector component 125 can query the data repository145 to select or otherwise identify the content item, e.g., from thecontent data 148. The content selector component 125 can also select thecontent item from the content provider computing device 155. For exampleresponsive to a query received from the data processing system 105, thecontent provider computing device 155 can provide a content item to thedata processing system 105 (or component thereof) for eventual output bythe client computing device 150.

The audio signal generator component 130 can generate or otherwiseobtain an output signal that includes the content item. For example, thedata processing system 105 can execute the audio signal generatorcomponent to generate or create an output signal corresponding to thecontent item. The interface 115 of the data processing system 105 canprovide or transmit one or more data packets that include the outputsignal via the computer network 165 to the client computing device 150.For example the data processing system 105 can provide the output signalfrom the data repository 145 or from the audio signal generatorcomponent 130 to the client computing device 150. The data processingsystem 105 can also instruct, via data packet transmissions, the contentprovider computing device 155 or the service provider computing device160 to provide the output signal to the client computing device 150. Theoutput signal can be obtained, generated, transformed to or transmittedas one or more data packets (or other communications protocol) from thedata processing system 105 (or other computing device) to the clientcomputing device 150.

The content selector component 125 can select the content item for theaction of the input audio signal as part of a real-time contentselection process. For example, the content item can be provided to theclient computing device for transmission as audio output in aconversational manner in direct response to the input audio signal. Thereal-time content selection process to identify the content item andprovide the content item to the client computing device 150 can occurwithin one minute or less from the time of the input audio signal and beconsidered real-time.

The output signal that corresponds to the content item, for example, anoutput signal that was obtained or generated by the audio signalgenerator component 130 transmitted via the interface 115 and thecomputer network 165 to the client computing device 150, can cause theclient computing device 150 to execute the audio driver 153 to drive thespeaker 154 to generate an acoustic wave corresponding to the outputsignal. The acoustic wave can include words of or corresponding to thecontent item.

The direct action API 135 of the data processing system can generate,based on the trigger keyword, action data structures. The direct actionAPI 135 can execute a specified action to satisfy the end user'sintention, as determined by the data processing system 105. Depending onthe action specified in its inputs, the direct action API 135 canexecute code or a dialog script that identifies the parameters requiredto fulfill a user request. The action data structures can be generatedresponsive to the request. The action data structure can be included inthe messages that are transmitted to or received by the service providercomputing device 160. Based on the request parsed by the NLP component110, the direct action API 135 can determine to which of the serviceprovider computing devices 160 the message should be sent. For example,if an input audio signal includes “order a taxi,” the NLP component 110can identify the trigger word “order” and the request for a taxi. Thedirect action API 135 can package the request into an action datastructure for transmission as a message to a service provider computingdevice 160 of a taxi service. The message can also be passed to thecontent selector component 125. The action data structure can includeinformation for completing the request. In this example, the informationcan include a pick up location and a destination location. The directaction API 135 can retrieve a template 149 from the repository 145 todetermine which fields to include in the action data structure. Thedirect action API 135 can determine necessary parameters and can packagethe information into an action data structure. The direct action API 135can retrieve content from the repository 145 to obtain information forthe fields of the data structure. The direct action API 135 can populatethe fields from the template with that information to generate the datastructure. The direct action API 135 can also populate the fields withdata from the input audio signal. The templates 149 can be standardizedfor categories of service providers or can be standardized for specificservice providers. For example, ride sharing service providers can usethe following standardized template 149 to create the data structure:{client_device_identifier; authentication_credentials; pick_up_location;destination_location; no_passengers; service_level}. The action datastructure can then be sent to another component such as the contentselector component 125 or to the service provider computing device 160to be fulfilled.

The direct action API 135 can communicate with the service providercomputing device 160 (that can be associated with the content item, suchas a car share company) to order a taxi or ride share vehicle for thelocation of the movie theater at the time the movie ends. The dataprocessing system 105 can obtain this location or time information aspart of the data packet (or other protocol) based data messagecommunication with the client computing device 150, from the datarepository 145, or from other sources such as the service providercomputing device 160 or the content provider computing device 155.Confirmation of this order (or other conversion) can be provided as anaudio communication from the data processing system 105 to the clientcomputing device 150 in the form of an output signal from the dataprocessing system 105 that drives the client computing device 150 torender audio output such as, “great, you will have a car waiting for youat 11 pm outside the theater.” The data processing system 105, via thedirect action API 135, can communicate with the service providercomputing device 160 to confirm the order for the car.

The data processing system 105 can obtain the response (e.g., “yesplease”) to the content item (“would you like a ride home from the movietheater?”) and can route a packet based data message to the serviceprovider NLP component 161 (or other component of the service providercomputing device). This packet based data message can cause the serviceprovider computing device 160 to effect a conversion, e.g., to make acar pick up reservation outside the movie theater. This conversion—orconfirmed order—(or any other conversion of any other action of thethread) can occur prior to completion of one or more actions of thethread, such as prior to completion of the movie, as well as subsequentto completion of one or more actions of the thread, such as subsequentto dinner.

The direct action API 135 can obtain content data 148 (or parameters 146or policies 147) from the data repository 145, as well as data receivedwith end user consent from the client computing device 150 to determinelocation, time, user accounts, logistical or other information in orderto reserve a car from the car share service. The content data 148 (orparameters 146 or policies 147) can be included in the action datastructure. When the content included in the action data structureincludes end user data that is used for authentication, the data can bepassed through a hashing function before being stored in the datarepository 145. Using the direct action API 135, the data processingsystem 105 can also communicate with the service provider computingdevice 160 to complete the conversion by, in this example, making thecar share pick up reservation.

The data processing system 105 can cancel actions associated withcontent items. The cancellation of the actions can be in response to thenetwork security appliance 123 generating an alarm condition. Thenetwork security appliance 123 can generate an alarm condition when thenetwork security appliance 123 predicts that the input audio signal ismalicious or otherwise not provided by an authorized end user of theclient computing device 150.

The data processing system 105 can include, interface, or otherwisecommunicate with a network security appliance 123. The network securityappliance 123 can authenticate signal transmissions between the clientcomputing device 150 and the content provider computing device 155. Thesignal transmissions can be the audio inputs from the client computingdevice 150 and the audio response signals from the client computingdevice 150. The audio response signals can be generated in response tocontent items transmitted to the client computing device 150 by the dataprocessing system 105 during one or more communication sessions. Thenetwork security appliance 123 can authenticate the signal transmissionby comparing the action data structure to one or more characteristics ofthe input audio signals and response audio signals.

The network security appliance 123 can determine characteristics of theinput audio signal. The characteristics of the audio signal can includevoiceprint, a keyword, a number of voices detected, an identification ofan audio source, and a location of an audio source. For example, thenetwork security appliance 123 can measure the spectral components ofthe input audio signal to generate a voiceprint of the voice used togenerate the input audio signal. The voiceprint generated in response tothe input audio signal can be compared to a stored voiceprint saved bythe data processing system 105. The saved voiceprint can be anauthenticated voiceprint—for example, a voiceprint generated by anauthenticated user of the client computing device 150 during a setupphase of the system.

The network security appliance 123 can also determine non-audiocharacteristics of the input audio signal. The client computing device150 can include non-audio information in the input audio signal. Thenon-audio information can be a location as determined or indicated bythe client computing device 150. The non-audio information can include aclient computing device 150 identifier. Non-audio characteristics orinformation can also include physical authentication devices such aschallenge-response with a one-time password device or a fingerprintreader.

The network security appliance 123 can set an alarm condition when thecharacteristics of the input audio signal do not correspond to theaction data structure. For example, the network security appliance 123can detect mismatches between the action data structure and thecharacteristics of the input audio signal. In one example, the inputaudio signal can include a location of the client computing device 150.The action data structure can include a predicted location of the enduser, such as a location based on the end user's smartphone's generallocation. If the network security appliance 123 determines that thelocation of the client computing device 150 is not within a predefinedrange of the location included in the action data structure, the networksecurity appliance 123 can set an alarm condition. In another example,the network security appliance 123 can compare the voiceprint of theinput audio signal to a voiceprint of the end user stored in the datarepository 145 and included in the action data structure. If the twovoiceprints do not match, the network security appliance 123 can set analarm condition.

The network security appliance 123 can determine which input audiosignal characteristics to base the authentication on responsive to therequest in the input audio signal. Authentication with the differentcharacteristics can have different computational requirements. Forexample, comparing voiceprints can be computationally more intensivethan comparing two locations. Selecting authentication methods that arecomputationally intensive when not called for can be computationallywasteful. The network security appliance 123 can improve the efficiencyof the data processing system 105 by selecting the characteristics usedfor authentication based on the request. For example, when the securityrisk associated with the input audio signal is low, the network securityappliance 123 can select an authentication method using a characteristicthat is not computationally intensive. The network security appliance123 can select the characteristic based on the cost required to completethe request. For example, a voiceprint characteristic can be used whenthe input audio signal is “order a new laptop computer,” but select alocation characteristic when the input audio signal is “order a taxi.”The selection of the characteristic can be based on the time orcomputational intensity required to complete the request.Characteristics that consume more computational resources can be used toauthenticate input audio signals that generate requests that take morecomputational resources to complete. For example, the input audio signalis “Ok, I'd like to go to dinner and the movies” can include multipleactions and requests and involve multiple service providers 160. Theinput audio signal can generate requests to search for possible movies,search for possible restaurant availability, make restaurantreservations, and purchase movie tickets. The completion of this inputaudio signal is both computationally more intensive and takes longer tocomplete than the input audio signal “Ok, what time is it?”

The network security appliance 123 can also set an alarm condition basedon the request included in the input audio signal. The network securityappliance 123 can automatically set an alarm condition if transmissionof the action data structure to a service provider computing device 160can result in a monetary charge to the end user of the client computingdevice 150. For example, a first input audio signal “Ok, order a pizza”can generate a monetary charge while a second input audio signal “Ok,what time is it” does not. In this example, the network securityappliance 123 can automatically set an alarm condition upon receiving anaction data structure corresponding to the first input audio signal andnot set an alarm condition up receiving an action data structurecorresponding to the second input audio signal.

The network security appliance 123 can set an alarm condition based onthe determination the action data structure is intended for a specificservice provider device 160. For example, the end user of the clientcomputing device 150 can set restrictions on which service providers thedata processing system 105 can interact with on the end user's behalfwithout further authorization. For example, if the end user has a child,to prevent the child from purchasing toys through a service providerthat sells toys, the end user can set a restriction that action datastructures cannot be transmitted to the toy seller without furtherauthentication. When the network security appliance 123 receives anaction data structure intended for a specific service provider device160, the network security appliance 123 can look up a policy in the datarepository to determine if an alarm condition should automatically beset.

The network security appliance 123 can send indications of the alarmcondition to the content selector component 125. The content selectorcomponent 125 can select a content item to transmit to the clientcomputing device 150. The content item can be an auditory request for apassphrase or additional information to authenticate the input audiosignal. The content item can be transmitted to the client computingdevice 150, where the audio driver 153 converts the content item intosound waves via the transducer 152. The client computing device 150 enduser can respond to the content item. The end user's response can bedigitized by the sensor 151 and transmitted to the data processingsystem 105. The NLP component 110 can process the response audio signaland provide the response to the network security appliance 123. Thenetwork security appliance 123 can compare a characteristic of theresponse audio signal with a characteristic of the input audio signal orthe action data structure. For example, the content item can be arequest for a passphrase. The NLP component 110 can recognize the textof the response audio signal and pass the text to the network securityappliance 123. The network security appliance 123 can run a hashfunction on the text. Having been hashed with the same hashing function,the end user's authenticated passphrase can be saved in the datarepository 145. The network security appliance 123 can compare thehashed text with the save, hashed passphrase. If the hashed text andhashed passphrase match, the network security appliance 123 canauthenticate the input audio signal. If the hashed text and the hashedpass phase do not match, the network security appliance 123 can set asecond alarm condition.

The network security appliance 123 can terminate communication sessions.The network security appliance 123 can transmit instructions to aservice provider computing device 160 to disable, pause, or otherwiseterminate a communication session established with the client computingdevice 150. The termination of the communication session can beresponsive to the network security appliance 123 setting a second alarmcondition. The network security appliance 123 can disable the computingdevice's ability to generate communication sessions via the dataprocessing system 105 with a service provider computing device 160. Forexample, if the network security appliance 123 sets a second alarmcondition responsive to the input audio signal “Ok, order a taxi,” thenetwork security appliance 123 can disable the ability of communicationsessions to be established between the client computing device 150 andthe taxi service provider device. An authorized user can reauthorize thetaxi service provider device at a later time.

FIG. 2 illustrates a flow diagram illustrating an example operation of asystem 200 to perform authentication of audio signals. The system 200can include one or more of the components or elements described above inrelation to system 100. For example, the system 200 can include a dataprocessing system 105 that is in communication with a client computingdevice 150 and a service provider computing device 160, via, forexample, the network 165.

The operation of the system 200 can begin with the client computingdevice 150 transmitting an input audio signal 201 to the data processingsystem 105. Once the data processing system 105 receives the input audiosignal, the NLP component 110 of the data processing system 105 canparse the input audio signal into a request and a trigger keyword thatcorresponds to the request. A communication session can be establishedbetween the client computing device 150 and the service providercomputing device 160, via the data processing system 105.

The direct action API 135 can generate an action data structure based onthe request. For example, the input audio signal can be “I want a rideto the movies.” In this example, the direct action API 135 can determinethe request is for a car service. The direct action API 135 candetermine the current location of the client computing device 150 thatgenerated the input audio signal and can determine the location of thenearest movie theater. The direct action API 135 can generate an actiondata structure that includes the location of the client computing device150 as the pickup location for the car service and includes the locationof the nearest movie theater as the destination of the car service. Theaction data structure can also include one or more characteristics ofthe input audio signal. The data processing system 105 can pass theaction data structure to the network security appliance to determinewhether an alarm condition should be set.

If the network security appliance detects an alarm condition, the dataprocessing system 105 can select, via the content selector component125, a content item. The data processing system 105 can provide thecontent item 202 to the client computing device 150. The content item202 can be provided to the client computing device 150 as part of acommunication session between the data processing system 105 and theclient computing device 150. The communication session can have the flowand feel of a real-time person to person conversation. For example, thecontent item can include audio signal that are played at the clientcomputing device 150. The end user can respond to the audio signal,which can be digitized by the sensor 151 and transmitted to the dataprocessing system 105. The content item can be a security question,content item, or other question that is transmitted to the clientcomputing device 150. The question can be presented, via the transducer152, to the end user that generated the input audio signal. In someimplementations, the security question can be based on past interactionbetween the client computing device 150 and the data processing system105. For example, if prior to the transmission of input audio signal,the user ordered a pizza via the system 200 by providing the input audiosignal of “Ok, order a pizza,” the security questions could include“what did you order for dinner last night.” The content item can alsoinclude a request for a password to be provided to the data processingsystem 105. The content item can include a push notification to a secondcomputing device 150 associated with the first computing device 150. Forexample, a push notification requesting confirmation of the input audiosignal can be sent to a smartphone associated with the client computingdevice 150. The user can select the push notification to confirm thatthe input audio signal is authentic.

During the communication session between the client computing device 150and the data processing system 105, the user can respond to the contentitem. The user can verbally respond to the content item. The responsecan be digitized by the sensor 151 and transmitted as a response audiosignal 203 carried by a plurality of data packets to the data processingsystem 105. The auditory signal can also include characteristics, whichcan be analyzed by the network security appliance. If the networksecurity appliance determines that an alarm condition persists based onthe conditions of the response audio signal, the network securityappliance can send a message 204 to the service provider computingdevice 160. The message 204 can include instructions for the serviceprovider computing device 160 to disable the communication session withthe client computing device 150.

FIG. 3 illustrates an example method 300 to authenticate packetizedaudio signals in a voice activated data packet (or other protocol) basedcomputer network environment. The method 300 can include receiving datapackets that include an input audio signal (ACT 302). For example, thedata processing system can execute, launch, or invoke the NLP componentto receive packet or other protocol based transmissions via the networkfrom the client computing device. The data packets can include orcorrespond to an input audio signal detected by the sensor, such as anend user saying “Ok, I would like to go to go dinner and then a movietonight” into a smartphone.

The method 300 can include identifying a request and a trigger keywordwithin the input audio signal (ACT 304). For example, the NLP componentcan parse the input audio signal to identify requests (such as “dinner”or “movie” in the above example) as well as trigger keywords “go” “goto” or “to go to” that correspond or relate to the request.

The method 300 can include generating a first action data structurebased on the request (ACT 306). The direct action API can generate adata structure that can be transmitted and processed by the serviceprovider computing device or content provider computing device to fulfilthe request of the input audio signal. For example, continuing the aboveexample the direct action API can generate a first action data structurethat is transmitted to a restaurant reservation service. The firstaction data structure can perform a search for a restaurant that islocated near the current location of the client computing device andthat meets other specifications associated with the user of the clientcomputing device (e.g., cuisine types preferred by the user of theclient computing device). The direct action API can also determine apreferred time for the reservation. For example, the data processingsystem can determine the restaurant selected during the search is 15minutes away and that the current time is 6:30 PM. The data processingsystem can set the preferred reservation time at a time after 6:45 PM.In this example, the first action data structure can include therestaurant name and the preferred reservation time. The data processingsystem can transmit the first action data structure to the serviceprovider computing device or the content provider computing device. ACT306 can include generating multiple action data structures. For theabove input audio signal, a second action data structure that includes amovie title and restaurant name can be generated and a third action datastructure that includes pick up and drop off locations can be generated.The data processing system can provide the second action data structureto a movie ticket reservation service and the third action datastructure to a car reservation service.

The method 300 can also include comparing the first action datastructure with a characteristic of the input audio signal (ACT 308). Thenetwork security appliance can compare the characteristic of the inputaudio signal to the first action data structure to determine theauthenticity of the input audio signal. Determining the authenticity ofthe input audio signal can include determining whether the person thatgenerated the input audio signal is authorized to generate input audiosignals. The characteristics of the input audio signal can include avoiceprint, a keyword, a number of voices detected, an identification ofan audio source (e.g., an identification of the sensor or clientcomputing device from where the input audio signal originated), alocation of an audio source, or the location of another client computingdevice (and the distance between the other client computing device andthe audio source). For example, an authorized voiceprint can begenerated during a setup phase by having a user speak passages. As thosepassages are spoken, the network security appliance can generate avoiceprint based on the frequency content, quality, duration, intensity,dynamics, and pitch of the signal. The network security appliance cangenerate an alarm condition if the network security appliance determinesthe characteristics of the input audio signal do not match the firstaction data structure or other expected data. For example, whengenerating an action data structure for “Ok, I would like to go to godinner and then a movie tonight,” the data processing system cangenerate an action data structure for a car reservation service thatincludes a pickup location based on the location of the user'ssmartphone. The action data structure can include the location. Theinput audio signal can be generated by an interactive speaker system.The location of the interactive speaker system transmitted to the dataprocessing system with the input audio signal. In this example, if thelocation of the user's smartphone does not match the location of theinteractive speaker system (or is not within a pre-defined distance ofthe interactive speaker system), then the user is not near theinteractive speaker system and the network security appliance candetermine the user most likely did not make the input audio signal. Thenetwork security appliance can generate an alarm condition. The distancebetween the client computing device 150 and a secondary client device(e.g., the end user's smartphone) can be calculated as a straight lineardistance between the two device, a driving distance between the twodevices. The distance can also be based on travel time between thelocations of the two devices. The distance may be based on othercharacteristics that can indicate location such as IP address and Wi-Finetwork locations.

The method 300 can include selecting a content item (ACT 310). Thecontent item can be based on the trigger keyword and the alarm conditionand can be selected via a real-time content selection process. Thecontent item can be selected to authenticate the input audio signal. Thecontent item can be a notification, online document, or message that isdisplayed on a client computing device, such as a user's smartphone. Thecontent item can be an audio signal that is transmitted to the clientcomputing device and broadcast to the user via the transducer. Thecontent item can be a security question. The security question can be apredefined security question, such as a request for a password. Thesecurity question can be dynamically generated. For example, thesecurity can be a question generated based on the prior history of theuser or client computing device.

The method 300 can include receiving data packets carrying auditorysignals (ACT 312). The data packets can carry auditory signalstransmitted between the client computing device and the conversationalAPI of the data processing system. The conversational API can establisha communication session with the data processing system responsive tointeraction with the content item. The auditory signals can include theuser's response to the content item transmitted to the client computingdevice during ACT 310. For example, the content item can cause theclient computing device to generate an audio signal asking “what is yourauthorization code”? The auditory signals can include the end userresponse to the content item. The end user response to the content itemcan be a characteristic of the response audio signal.

The method 300 can also include comparing a characteristic of theresponse audio signal with a characteristic of the input audio signal(ACT 314). The response audio signal can include a passphrase or othercharacteristics. The content item can include instructions for theclient computing device to capture one or more specific characteristicsof the response audio signal. For example, the characteristic of theinput audio signal can be a location of the client computing device. Thecharacteristic of the response audio signal can be different than thecharacteristic of the input audio signal. For example, thecharacteristic of the response audio signal can be a voiceprint. Thecontent item can include instructions for capturing the voiceprintcharacteristic. The instructions can include capturing the responseaudio signal at a higher sampling frequency so that additional frequencycontent can be analyzed for the voiceprint. If the system does notdetect a match between the characteristics of the response audio signaland the input audio signal, the system can set an alarm condition. Forexample, if the characteristics of the response audio signal include apassphrase that does not match a passphrase associated with the inputaudio signal, the alarm condition can be set.

If the characteristics of the response audio signal matches thecharacteristic of the input audio signal (e.g., the passphrases (orhashes thereof) match). A pass condition can be set. When a passcondition is set, the system can transmit instructions to a third-partto continue the communication session with the client device. Theinstructions to continue the communication session can authenticate thecommunication session for a predetermined amount of time such that thecommunication session does not need to be reauthenticated untilexpiration of the predetermined time.

The method 300 can also include transmitting an instruction to athird-party provider device to disable the communication session (ACT316). Disabling the communication session can prevent messages andaction data structures from being transmitted to the service providerdevice. This can improve network utilization by decreasing unwantednetwork traffic. Disabling the communication session can reducecomputational waste because the service provider devices does notprocess requests that are malicious or generated in error.

FIG. 4 is a block diagram of an example computer system 400. Thecomputer system or computing device 400 can include or be used toimplement the system 100 or its components such as the data processingsystem 105. The computing system 400 includes a bus 405 or othercommunication component for communicating information and a processor410 or processing circuit coupled to the bus 405 for processinginformation. The computing system 400 can also include one or moreprocessors 410 or processing circuits coupled to the bus for processinginformation. The computing system 400 also includes main memory 415,such as a random access memory (RAM) or other dynamic storage device,coupled to the bus 405 for storing information, and instructions to beexecuted by the processor 410. The main memory 415 can be or include thedata repository 145. The main memory 415 can also be used for storingposition information, temporary variables, or other intermediateinformation during execution of instructions by the processor 410. Thecomputing system 400 may further include a read only memory (ROM) 420 orother static storage device coupled to the bus 405 for storing staticinformation and instructions for the processor 410. A storage device425, such as a solid state device, magnetic disk or optical disk, can becoupled to the bus 405 to persistently store information andinstructions. The storage device 425 can include or be part of the datarepository 145.

The computing system 400 may be coupled via the bus 405 to a display435, such as a liquid crystal display, or active matrix display, fordisplaying information to a user. An input device 430, such as akeyboard including alphanumeric and other keys, may be coupled to thebus 405 for communicating information and command selections to theprocessor 410. The input device 430 can include a touch screen display435. The input device 430 can also include a cursor control, such as amouse, a trackball, or cursor direction keys, for communicatingdirection information and command selections to the processor 410 andfor controlling cursor movement on the display 435. The display 435 canbe part of the data processing system 105, the client computing device150 or other component of FIG. 1, for example.

The processes, systems and methods described herein can be implementedby the computing system 400 in response to the processor 410 executingan arrangement of instructions contained in main memory 415. Suchinstructions can be read into main memory 415 from anothercomputer-readable medium, such as the storage device 425. Execution ofthe arrangement of instructions contained in main memory 415 causes thecomputing system 400 to perform the illustrative processes describedherein. One or more processors in a multi-processing arrangement mayalso be employed to execute the instructions contained in main memory415. Hard-wired circuitry can be used in place of or in combination withsoftware instructions together with the systems and methods describedherein. Systems and methods described herein are not limited to anyspecific combination of hardware circuitry and software.

Although an example computing system has been described in FIG. 4, thesubject matter including the operations described in this specificationcan be implemented in other types of digital electronic circuitry, or incomputer software, firmware, or hardware, including the structuresdisclosed in this specification and their structural equivalents, or incombinations of one or more of them.

For situations in which the systems discussed herein collect personalinformation about users, or may make use of personal information, theusers may be provided with an opportunity to control whether programs orfeatures that may collect personal information (e.g., information abouta user's social network, social actions or activities, a user'spreferences, or a user's location), or to control whether or how toreceive content from a content server or other data processing systemthat may be more relevant to the user. In addition, certain data may beanonymized in one or more ways before it is stored or used, so thatpersonally identifiable information is removed when generatingparameters. For example, a user's identity may be anonymized so that nopersonally identifiable information can be determined for the user, or auser's geographic location may be generalized where location informationis obtained (such as to a city, postal code, or state level), so that aparticular location of a user cannot be determined. Thus, the user mayhave control over how information is collected about him or her and usedby the content server.

The subject matter and the operations described in this specificationcan be implemented in digital electronic circuitry, or in computersoftware, firmware, or hardware, including the structures disclosed inthis specification and their structural equivalents, or in combinationsof one or more of them. The subject matter described in thisspecification can be implemented as one or more computer programs, e.g.,one or more circuits of computer program instructions, encoded on one ormore computer storage media for execution by, or to control theoperation of, data processing apparatuses. Alternatively or in addition,the program instructions can be encoded on an artificially generatedpropagated signal, e.g., a machine-generated electrical, optical, orelectromagnetic signal that is generated to encode information fortransmission to suitable receiver apparatus for execution by a dataprocessing apparatus. A computer storage medium can be, or be includedin, a computer-readable storage device, a computer-readable storagesubstrate, a random or serial access memory array or device, or acombination of one or more of them. While a computer storage medium isnot a propagated signal, a computer storage medium can be a source ordestination of computer program instructions encoded in an artificiallygenerated propagated signal. The computer storage medium can also be, orbe included in, one or more separate components or media (e.g., multipleCDs, disks, or other storage devices). The operations described in thisspecification can be implemented as operations performed by a dataprocessing apparatus on data stored on one or more computer-readablestorage devices or received from other sources.

The terms “data processing system” “computing device” “component” or“data processing apparatus” encompass various apparatuses, devices, andmachines for processing data, including by way of example a programmableprocessor, a computer, a system on a chip, or multiple ones, orcombinations of the foregoing. The apparatus can include special purposelogic circuitry, e.g., an FPGA (field programmable gate array) or anASIC (application specific integrated circuit). The apparatus can alsoinclude, in addition to hardware, code that creates an executionenvironment for the computer program in question, e.g., code thatconstitutes processor firmware, a protocol stack, a database managementsystem, an operating system, a cross-platform runtime environment, avirtual machine, or a combination of one or more of them. The apparatusand execution environment can realize various different computing modelinfrastructures, such as web services, distributed computing and gridcomputing infrastructures. The direct action API 135, content selectorcomponent 125, network security appliance 123, or NLP component 110 andother data processing system 105 components can include or share one ormore data processing apparatuses, systems, computing devices, orprocessors.

A computer program (also known as a program, software, softwareapplication, app, script, or code) can be written in any form ofprogramming language, including compiled or interpreted languages,declarative or procedural languages, and can be deployed in any form,including as a stand-alone program or as a module, component,subroutine, object, or other unit suitable for use in a computingenvironment. A computer program can correspond to a file in a filesystem. A computer program can be stored in a portion of a file thatholds other programs or data (e.g., one or more scripts stored in amarkup language document), in a single file dedicated to the program inquestion, or in multiple coordinated files (e.g., files that store oneor more modules, sub-programs, or portions of code). A computer programcan be deployed to be executed on one computer or on multiple computersthat are located at one site or distributed across multiple sites andinterconnected by a communication network.

The processes and logic flows described in this specification can beperformed by one or more programmable processors executing one or morecomputer programs (e.g., components of the data processing system 105)to perform actions by operating on input data and generating output. Theprocesses and logic flows can also be performed by, and apparatuses canalso be implemented as, special purpose logic circuitry, e.g., an FPGA(field programmable gate array) or an ASIC (application-specificintegrated circuit). Devices suitable for storing computer programinstructions and data include all forms of non-volatile memory, mediaand memory devices, including by way of example semiconductor memorydevices, e.g., EPROM, EEPROM, and flash memory devices; magnetic disks,e.g., internal hard disks or removable disks; magneto optical disks; andCD ROM and DVD-ROM disks. The processor and the memory can besupplemented by, or incorporated in, special purpose logic circuitry.

The subject matter described herein can be implemented in a computingsystem that includes a back-end component, e.g., as a data server, orthat includes a middleware component, e.g., an application server, orthat includes a front-end component, e.g., a client computer having agraphical user interface or a web browser through which a user caninteract with an implementation of the subject matter described in thisspecification, or a combination of one or more such back-end,middleware, or front-end components. The components of the system can beinterconnected by any form or medium of digital data communication,e.g., a communication network. Examples of communication networksinclude a local area network (“LAN”) and a wide area network (“WAN”), aninter-network (e.g., the Internet), and peer-to-peer networks (e.g., adhoc peer-to-peer networks).

The computing system such as system 100 or system 400 can includeclients and servers. A client and server are generally remote from eachother and typically interact through a communication network (e.g., thenetwork 165). The relationship of client and server arises by virtue ofcomputer programs running on the respective computers and having aclient-server relationship to each other. In some implementations, aserver transmits data (e.g., data packets representing a content item)to a client device (e.g., for purposes of displaying data to andreceiving user input from a user interacting with the client device).Data generated at the client device (e.g., a result of the userinteraction) can be received from the client device at the server (e.g.,received by the data processing system 105 from the client computingdevice 150 or the content provider computing device 155 or the serviceprovider computing device 160).

While operations are depicted in the drawings in a particular order,such operations are not required to be performed in the particular ordershown or in sequential order, and all illustrated operations are notrequired to be performed. Actions described herein can be performed in adifferent order.

The separation of various system components does not require separationin all implementations, and the described program components can beincluded in a single hardware or software product. For example, the NLPcomponent 110, the content selector component 125, or the networksecurity appliance 123 can be a single component, app, or program, or alogic device having one or more processing circuits, or part of one ormore servers of the data processing system 105.

Having now described some illustrative implementations, it is apparentthat the foregoing is illustrative and not limiting, having beenpresented by way of example. In particular, although many of theexamples presented herein involve specific combinations of method actsor system elements, those acts and those elements may be combined inother ways to accomplish the same objectives. Acts, elements andfeatures discussed in connection with one implementation are notintended to be excluded from a similar role in other implementations orimplementations.

The phraseology and terminology used herein is for the purpose ofdescription and should not be regarded as limiting. The use of“including” “comprising” “having” “containing” “involving”“characterized by” “characterized in that” and variations thereofherein, is meant to encompass the items listed thereafter, equivalentsthereof, and additional items, as well as alternate implementationsconsisting of the items listed thereafter exclusively. In oneimplementation, the systems and methods described herein consist of one,each combination of more than one, or all of the described elements,acts, or components.

Any references to implementations or elements or acts of the systems andmethods herein referred to in the singular may also embraceimplementations including a plurality of these elements, and anyreferences in plural to any implementation or element or act herein mayalso embrace implementations including only a single element. Referencesin the singular or plural form are not intended to limit the presentlydisclosed systems or methods, their components, acts, or elements tosingle or plural configurations. References to any act or element beingbased on any information, act or element may include implementationswhere the act or element is based at least in part on any information,act, or element.

Any implementation disclosed herein may be combined with any otherimplementation or embodiment, and references to “an implementation,”“some implementations,” “one implementation” or the like are notnecessarily mutually exclusive and are intended to indicate that aparticular feature, structure, or characteristic described in connectionwith the implementation may be included in at least one implementationor embodiment. Such terms as used herein are not necessarily allreferring to the same implementation. Any implementation may be combinedwith any other implementation, inclusively or exclusively, in any mannerconsistent with the aspects and implementations disclosed herein.

References to “or” may be construed as inclusive so that any termsdescribed using “or” may indicate any of a single, more than one, andall of the described terms. For example, a reference to “at least one of‘A’ and ‘B’” can include only ‘A’, only ‘B’, as well as both ‘A’ and‘B’. Such references used in conjunction with “comprising” or other openterminology can include additional items.

Where technical features in the drawings, detailed description or anyclaim are followed by reference signs, the reference signs have beenincluded to increase the intelligibility of the drawings, detaileddescription, and claims. Accordingly, neither the reference signs northeir absence have any limiting effect on the scope of any claimelements.

The systems and methods described herein may be embodied in otherspecific forms without departing from the characteristics thereof. Theforegoing implementations are illustrative rather than limiting of thedescribed systems and methods. Scope of the systems and methodsdescribed herein is thus indicated by the appended claims, rather thanthe foregoing description, and changes that come within the meaning andrange of equivalency of the claims are embraced therein.

The invention claimed is:
 1. A system to authenticate packetized audiosignals in a voice activated computer network environment, comprising: adata processing system comprising at least one processor and memory; anatural language processor component executed by the data processingsystem to receive, via an interface of the data processing system, datapackets comprising an input audio signal detected by a sensor of aclient device; the natural language processor component to parse theinput audio signal to identify a request and a trigger keywordcorresponding to the request; a direct action application programminginterface of the data processing system to generate, based on thetrigger keyword, a first action data structure responsive to therequest; a network security appliance to authenticate the input audiosignal detected by the sensor of the client device based on acharacteristic of the input audio signal and the first action datastructure generated by the direct action application programminginterface; the direct action application programming interface toidentify an account based on the input audio signal authenticated by thenetwork security appliance, and transmit, to a third-party providerdevice, the first action data structure responsive to the networksecurity appliance authenticating the input audio signal based on thecharacteristic of the input audio signal and the first action datastructure, receipt of the first action data structure by the third-partyprovider device causing the third-party provider device to execute thefirst action data structure; receive second data packets comprising asecond input audio signal detected by the sensor of the client device;generate an alarm condition responsive to a second characteristic of thesecond input audio signal not matching a parameter associated with thefirst action data structure; and transmit, responsive to generation ofthe alarm condition, an instruction to the third-party provider deviceto terminate a communication session associated with, or execution of,the first action data structure.
 2. The system of claim 1, comprising:the network security appliance to authenticate the input audio signalbased on the characteristic of the input audio signal, thecharacteristic including at least one a voiceprint.
 3. The system ofclaim 1, comprising the network security appliance to: measure aspectral component of the input audio signal to identify a voiceprint;compare the spectral component with a stored voiceprint generated duringa setup phase; and authenticate the input audio signal based on thecomparison of the spectral component with the stored voiceprint.
 4. Thesystem of claim 1, comprising the network security appliance to:determine the characteristic of the input audio signal based on alocation of the client device; and authenticate the input audio signalbased on the location of the client device.
 5. The system of claim 1,comprising the network security appliance to: determine thecharacteristic of the input audio signal with a physical authenticationdevice; and authenticate the input audio signal based on a response fromthe physical authentication device.
 6. The system of claim 1, comprisingthe network security appliance to: determine the characteristic of theinput audio signal based on a number of voices detected in the inputaudio signal; and authenticate the input audio signal based on thenumber of voices detected.
 7. The system of claim 1, comprising thenetwork security appliance to: receive a third input audio signaldetected by the sensor of the client device; detect, based on acharacteristic of the third input audio signal, a second alarmcondition; and prevent, responsive to the second alarm condition,execution of a third action data structure based on the third inputaudio signal.
 8. The system of claim 1, comprising the data processingsystem to: perform a search based on the first action data structure andthe characteristic of the input audio signal authenticated by thenetwork security appliance.
 9. The system of claim 1, comprising thedata processing system to: identify the account based on thecharacteristic of the input audio signal; identify a preferenceassociated with the account; and perform a search based on thepreference.
 10. The system of claim 1, comprising the data processingsystem to: identify the account based on the characteristic of the inputaudio signal; identify a first preference associated with the account;perform a first search based on the first preference; identify a secondaccount based on the characteristic of the second input audio signaldetected by the sensor of the client device; identify a secondpreference associated with the second account; and perform a secondsearch based on the second preference.
 11. A method of authenticatingpacketized audio signals in a voice activated computer networkenvironment, comprising: receiving, by a data processing systemcomprising at least one processor and memory that executes a naturallanguage processor component, via an interface of the data processingsystem, data packets comprising an input audio signal detected by asensor of a client device; parsing, by the natural language processorcomponent, the input audio signal to identify a request and a triggerkeyword corresponding to the request; generating, by a direct actionapplication programming interface of the data processing system, basedon the trigger keyword, a first action data structure responsive to therequest; authenticating, by a network security appliance, the inputaudio signal detected by the sensor of the client device based on acharacteristic of the input audio signal and the first action datastructure generated by the direct action application programminginterface; and identifying, by the data processing system, an accountbased on the input audio signal authenticated by the network securityappliance; transmitting, by the data processing system, to a third-partyprovider device, the first action data structure responsive to thenetwork security appliance authenticating the input audio signal basedon the characteristic of the input audio signal and the first actiondata structure, receipt of the first action data structure by thethird-party provider device causing the third-party provider device toexecute the first action data structure; receiving, by the dataprocessing system, second data packets comprising a second input audiosignal detected by the sensor of the client device; generating, by thedata processing system, an alarm condition responsive to a secondcharacteristic of the second input audio signal not matching a parameterassociated with the first action data structure; and transmitting, bythe data processing system, responsive to generation of the alarmcondition, an instruction to the third-party provider device toterminate a communication session associated with, or execution of, thefirst action data structure.
 12. The method of claim 11, comprising:authenticating, by the network security appliance, the input audiosignal based on the characteristic of the input audio signal, thecharacteristic including at least one a voiceprint.
 13. The method ofclaim 11, comprising: measuring a spectral component of the input audiosignal to identify a voiceprint; comparing the spectral component with astored voiceprint generated during a setup phase; and authenticating theinput audio signal based on the comparing of the spectral component withthe stored voiceprint.
 14. The method of claim 11, comprising:determining the characteristic of the input audio signal based on alocation of the client device; and authenticating the input audio signalbased on the location of the client device.
 15. The method of claim 11,comprising: determining the characteristic of the input audio signalwith a physical authentication device; and authenticating the inputaudio signal based on a response from the physical authenticationdevice.
 16. The method of claim 11, comprising: determining thecharacteristic of the input audio signal based on a number of voicesdetected in the input audio signal; and authenticating the input audiosignal based on the number of voices detected.
 17. The method of claim11, comprising: receive a third input audio signal detected by thesensor of the client device; detect, based on a characteristic of thethird input audio signal, a second alarm condition; and prevent,responsive to the second alarm condition, execution of a third actiondata structure based on the third input audio signal.
 18. The method ofclaim 11, comprising: performing a search based on the first action datastructure and the characteristic of the input audio signal authenticatedby the network security appliance.
 19. The method of claim 11,comprising: identifying the account based on the characteristic of theinput audio signal; identifying a preference associated with theaccount; and performing a search based on the preference.
 20. The methodof claim 11, comprising: identifying the account based on thecharacteristic of the input audio signal; identifying a first preferenceassociated with the account; performing a first search based on thefirst preference; identifying a second account based on thecharacteristic of the second input audio signal detected by the sensorof the client device; identifying a second preference associated withthe second account; and performing a second search based on the secondpreference.